Dose-Response Effects of the Text4baby Mobile Health Program: Randomized Controlled Trial
Open accessAbstract
BACKGROUND: Mobile health (mHealth) is growing rapidly, but more studies are needed on how to optimize programs, including optimal timing of messaging, dose of exposure, and value of interactive features. This study evaluates final outcomes of text4baby (a text message service for pregnant and postpartum women) from a randomized trial performed in a population of pregnant female soldiers and family members. OBJECTIVE: The study aims were to evaluate (1) treatment effects and (2) dose-response effects of text4baby on behavioral outcomes compared to control (no text4baby) condition. METHODS: The study was a randomized trial of text4baby at Madigan Army Medical Center. Female military health beneficiaries who met inclusion criteria were eligible for the study. Participants provided consent, completed a baseline questionnaire, and then were randomized to enroll in text4baby or not. They were followed up at 3 time points thereafter through delivery of their baby. Generalized estimating equation models were used to evaluate outcomes. We examined treatment effects and the effects of higher doses of text4baby messages on outcomes. RESULTS: We report descriptive statistics including dosage of text messages delivered. The main finding was a significant effect of high exposure to text4baby on self-reported alcohol consumption postpartum (OR 0.212, 95% CI 0.046-0.973, P=.046), as measured by the question "Since you found out about your pregnancy, have you consumed alcoholic beverages?" The text4baby participants also reported lower quantities of alcohol consumed postpartum. CONCLUSIONS: Studies of text4baby have helped to build the mHealth evidence base. The effects of text4baby offer lessons for future scalable mHealth programs and suggest the need to study dose-response effects of these interventions.
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The dose design of app-based interventions has been suggested as an important aspect that profoundly influences intervention effects.
“The dose design of app-based interventions has been suggested as an important aspect that profoundly influences intervention effects [13,24,53].”
From Effectiveness and Minimum Effective Dose of App-Based Mobile Health Interventions for Anxiety and Depression Symptom Reduction: Systematic Review and Meta-Analysis (2022) · cites this paper as [53]
The Discussion reports a dose-response effect in Text4baby and says that understanding optimal dosage could improve mHealth outcomes. But this was a text-message intervention, not an app-based one, and the authors limit their observed dosage effect to alcohol use rather than intervention effects generally (Discussion; page not available). (LLM, conf=0.84)
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Interventions Promoting Early Social-Emotional Development
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Telemedicine and mHealth odyssey: a journey from the battlefield to academia
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- Authors
- Evans, W., Nielsen, P. E., Szekely, D. R., Bihm, J. W., Murray, E. A., Snider, J., & Abroms, L. C.
- Affiliations
- George Washington University (US)
- General Leonard Wood Army Community Hospital (US)
- Madigan Army Medical Center (US)
- University of Washington (US)
- Corresponding author
- Evans, William
- Venue
- JMIR mHealth and uHealth
- Publisher
- JMIR Publications Inc.
- Published
- 2015-01-28
- Volume
- 3
- Issue
- 1
- Pages
- e12
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC4327187
- OpenAlex
- W2146373152
- Cited by
- 86
- References
- 41
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 11 · 2022: 10 · 2021: 12 · 2020: 9 · 2019: 6 · 2018: 8 · 2017: 7 · 2016: 9 · 2015: 2
- FWCI
- 15.85
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Agency for Healthcare Research and Quality (T32HS013853)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Health › Social Media in Health Education
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health, text messaging, dose-response relationship, pregnant women, postpartum women, military families, alcohol consumption, maternal alcohol use, health behavior change
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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.
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