Evidence map›Paper›PMID 29674313›Full record

ArticleJMIR mHealth and uHealth2018

Key Lessons and Impact of the Growing Healthy mHealth Program on Milk Feeding, Timing of Introduction of Solids, and Infant Growth: Quasi-Experimental Study.

Rachel A Laws, Elizabeth A Denney-Wilson, Sarah Taki, Catherine G Russell, Miaobing Zheng, Eloise-Kate Litterbach, Kok-Leong Ong, Sharyn J Lymer, Rosalind Elliott, Karen J Campbell

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 5 pooled it
8.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 5 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  13. Improving Breastfeeding by Empowering Mothers in Vietnam: A Randomised Controlled Trial of a Mobile App.International journal of environmental research and public health · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Rachel A LawsInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID http://orcid.org/0000-0003-4328-1116
Elizabeth A Denney-WilsonCentre for Obesity Management and Prevention Research Excellence in Primary Health Care, Sydney, Australia.ORCID http://orcid.org/0000-0001-9879-4969
Sarah TakiCentre for Obesity Management and Prevention Research Excellence in Primary Health Care, Sydney, Australia.ORCID http://orcid.org/0000-0002-7228-8993
Catherine G RussellCentre for Obesity Management and Prevention Research Excellence in Primary Health Care, Sydney, Australia.ORCID http://orcid.org/0000-0002-0848-2724
Miaobing ZhengInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID http://orcid.org/0000-0002-4151-3502
Eloise-Kate LitterbachInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID http://orcid.org/0000-0002-4618-1068
Kok-Leong OngLa Trobe Analytics Lab, La Trobe University, Melbourne, Australia.ORCID http://orcid.org/0000-0003-4688-7674
Sharyn J LymerCentre for Obesity Management and Prevention Research Excellence in Primary Health Care, Sydney, Australia.ORCID http://orcid.org/0000-0002-7876-6722
Rosalind ElliottCentre for Obesity Management and Prevention Research Excellence in Primary Health Care, Sydney, Australia.ORCID http://orcid.org/0000-0002-9239-7126
Karen J CampbellInstitute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.ORCID http://orcid.org/0000-0002-4499-3396
Deakin University · AUUniversity of Technology Sydney · AUThe University of Sydney · AULa Trobe University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe first year of life is an important window to initiate healthy infant feeding practices to promote healthy growth. Interventions delivered by mobile phone (mHealth) provide a novel approach for reaching parents; however, little is known about the effectiveness of mHealth for child obesity prevention.

objectiveThe objective of this study was to determine the feasibility and effectiveness of an mHealth obesity prevention intervention in terms of reach, acceptability, and impact on key infant feeding outcomes.

methodsA quasi-experimental study was conducted with an mHealth intervention group (Growing healthy) and a nonrandomized comparison group (Baby's First Food). The intervention group received access to a free app and website containing information on infant feeding, sleep and settling, and general support for parents with infants aged 0 to 9 months. App-generated notifications directed parents to age-and feeding-specific content within the app. Both groups completed Web-based surveys when infants were less than 3 months old (T1), at 6 months of age (T2), and 9 months of age (T3). Survival analysis was used to examine the duration of any breastfeeding and formula introduction, and cox proportional hazard regression was performed to examine the hazard ratio for ceasing breast feeding between the two groups. Multivariate logistic regression with adjustment for a range of child and parental factors was used to compare the exclusive breastfeeding, formula feeding behaviors, and timing of solid introduction between the 2 groups. Mixed effect polynomial regression models were performed to examine the group differences in growth trajectory from birth to T3.

resultsA total of 909 parents initiated the enrollment process, and a final sample of 645 parents (Growing healthy=301, Baby's First Food=344) met the eligibility criteria. Most mothers were Australian born and just under half had completed a university education. Retention of participants was high (80.3%, 518/645) in both groups. Most parents (226/260, 86.9%) downloaded and used the app; however, usage declined over time. There was a high level of satisfaction with the program, with 86.1% (143/166) reporting that they trusted the information in the app and 84.6% (170/201) claiming that they would recommend it to a friend. However, some technical problems were encountered with just over a quarter of parents reporting that the app failed to work at times. There were no significant differences between groups in any of the target behaviors. Growth trajectories also did not differ between the 2 groups.

conclusionsAn mHealth intervention using a smartphone app to promote healthy infant feeding behaviors is a feasible and acceptable mode for delivering obesity prevention intervention to parents; however, app usage declined over time. Learnings from this study will be used to further enhance the program so as to improve its potential for changing infant feeding behaviors.

Indexed as

breastfeedingcomplementary feedingformula feedinginfancymHealthobesity preventionparents

Identifiers

PMID29674313
PMCPMC5934537
OpenAlexW2800950148

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.