A Mixed Methods Study to Explore the Effects of Program Design Elements and Participant Characteristics on Parents' Engagement With an mHealth Program to Promote Healthy Infant Feeding: The Growing Healthy Program
Open accessAbstract
Purpose Mobile health (mHealth) interventions have great potential to promote health. To increase consumer engagement in mHealth interventions it is necessary to address factors that influence the target demographic. The Growing healthy (GH) program is the first obesity prevention program delivered via a smartphone app and website offering evidence-based information on infant feeding from birth until 9 months of age. This sub-study aimed to explore how the design features, quality of the app and participant characteristics influenced parents’ engagement with the GH app. Methods A sequential mixed methods design was used. The GH app participants (225/301) were considered for this sub-study. Participant app engagement was measured through a purpose-built Engagement Index (EI) using app metrics. Participants were categorised as low, moderately or highly engaged based on their EI score upon completing the 9 month program and were then invited to participate in semi-structured telephone interviews. Participants who used the app program, given an EI score and expressed interest to participate in these interviews were eligible. The interviews explored factors that influenced app engagement including delivery features and quality. Thematic analysis networks was used for analysis. Results 108/225 expressed interest and 18 interviews were conducted from low (n=3), moderately (n=7) or highly (n=8) engaged participants based on purposeful sampling. Participants defined as highly engaged were likely to be a first-time parent, felt the app content to be trustworthy and the app design facilitated easy navigation and regularly opened the push notifications. Participants defined as having low or moderate engagement were likely to have experience from previous children, felt they had sufficient knowledge on infant feeding and the app did not provide further information, or experienced technological issues including app dysfunction due to system upgrades. Conclusions/implications This study demonstrated a novel approach to comprehensively analyse engagement in an mHealth intervention through quantitative (Engagement Index) and qualitative (interviews) methods. It provides an insight on maximising data collected from these programs for measuring effectiveness and to understand users of various engagement levels interaction with program features. Measuring this can determine efficacy and refine programs to meet user requirements.
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Some users wanted a credible source, a trustworthy and evidence-based guide with references to the information they receive.
“Some users wanted a credible source, a trustworthy and evidence-based guide with references to the information they receive (Q8) [62,70,73].”
From Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review (2020) · cites this paper as [70]
The Quality > Trustworthiness section reports that participants regarded the infant-feeding app as a trustworthy source of information, and Discussion > Quality links that perception to its university endorsement and health-practitioner referrals. These passages support the desire for credible information, but they do not report that users wanted an evidence-based guide with references to the information they received. (LLM, conf=0.84)
Experimental — accuracy not yet measuredReminders positively affected behavioral regulation by prompting engagement with self-monitoring and the tracking features of the app.
“Reminders positively affected behavioral regulation by prompting engagement with self-monitoring and the tracking features of the app (Q14) [37,39,40,51,54,62,67,69-71] as well as reinforcing the users by reminding them about their positive progress [40,48,51].”
From Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review (2020) · cites this paper as [70]
In “Modes of Delivery > Push Notifications” (page unavailable), the paper reports that notifications prompted parents to access the app and engage with its other features. It does not establish that they prompted use of self-monitoring or tracking features, or improved behavioral regulation. (LLM, conf=0.86)
Experimental — accuracy not yet measuredEvidence for the importance of embedded social media for engagement has been mixed.
“Evidence for the importance of embedded social media for engagement has been mixed [39,40,48,54,56,58,61,66, 67,70-72,75].”
From Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review (2020) · cites this paper as [70]
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- Authors
- Taki, S., Russell, C. G., Lymer, S., Laws, R., Campbell, K., Appleton, J., Ong, K.-L., & Denney-Wilson, E.
- Affiliations
- University of Technology Sydney (AU)
- Deakin University (AU)
- The University of Sydney (AU)
- La Trobe University (AU)
- Corresponding author
- Taki, Sarah
- ORCID
- Venue
- Frontiers in Endocrinology
- Publisher
- Frontiers Media SA
- Published
- 2019-06-25
- Volume
- 10
- Pages
- 397-397
- ISSN
- 1664-2392 (ISSN-L)
- PMC
- PMC6603091
- OpenAlex
- W2955250457
- Cited by
- 24
- References
- 63
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 3 · 2022: 6 · 2020: 7
- FWCI
- 4.43
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Endocrinology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Own your potential (DEAKIN) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Funders
- Department of Health and Ageing, Australian Government
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health, app engagement, infant feeding, obesity prevention, mobile application design, engagement index, participant characteristics, parental engagement, app quality, trust in health information, push notifications, technical challenges, user experience
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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