Accepted for/Published in: JMIR Pediatrics and Parenting
Date Submitted: Sep 30, 2018
Open Peer Review Period: Oct 6, 2018 - Nov 22, 2018
Date Accepted: Mar 24, 2019
(closed for review but you can still tweet)
Identification and evaluation of features and educational content related to milk production in breastfeeding apps using novel scoresheets informed by Social Cognitive Theory
ABSTRACT
Background:
Low milk production is one of the main reasons for premature breastfeeding cessation. Smartphone apps have the potential to assist mothers with promoting, interpreting, tracking, or learning about milk production. It is not known whether breastfeeding apps contain high-quality, engaging, and diverse content and features that could be used by mothers to increase their breastfeeding self-efficacy and answer their questions about milk production.
Objective:
The overarching objective of this study was to identify and evaluate features and content within breastfeeding apps that could be used by mothers to increase breastfeeding self-efficacy and answer their questions about milk production. The secondary objectives were to quantify the diversity of representation of breastfeeding experiences within breastfeeding apps and to define the type of organization that is most likely to create free apps and apps with high-quality, engaging, and diverse features and content related to milk production.
Methods:
Breastfeeding apps were identified in the App Store (iOS). All features that assist mothers with tracking, promoting, or interpreting milk production in the first zero to six months postpartum were noted. Every screen containing educational information about milk production was identified and saved for review. Images of mothers and caretakers within the selected screenshots were assessed. Three scoresheets informed by Social Cognitive Theory were created to evaluate all identified features, educational content, and images representing the breastfeeding experience.
Results:
Forty-one breastfeeding apps were reviewed. Only seven apps contained both features and educational content related to milk production. Thirteen apps that contained educational content related to milk production received a mean combined content and diversity score of 15.3 out 78. Out of the 48 photos reviewed within screenshots that contain milk production educational content, 87.5% (n = 42) were of White women and their infants. For-profit companies and large organizations were most likely to create free apps and apps that received high scores on the combined content and diversity or features scoresheet, respectively.
Conclusions:
Features and educational content related to milk production and breastfeeding imagery within breastfeeding apps were evaluated using three novel scoresheets informed by Social Cognitive Theory. Very few apps contained both features that promote breastfeeding self-efficacy and high-quality engaging educational content with images of diverse caretakers. Thus, it is likely that parents, especially those from minority or low-income groups, have limited options when selecting a breastfeeding app. App developers could use the scoresheets and findings in this review to develop breastfeeding apps that assist mothers with interpreting, tracking, or learning about milk production through high-quality, engaging features, content, and imagery.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.