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Published on in Vol 8 (2025)

This is a member publication of University of Pittsburgh

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65247, first published .
Pregnant woman looking at her phone in a dimly lit room

Integrating Infant Safe Sleep and Breastfeeding Education Into an App in a Novel Approach to Reaching High-Risk Populations: Prospective Observational Study

Integrating Infant Safe Sleep and Breastfeeding Education Into an App in a Novel Approach to Reaching High-Risk Populations: Prospective Observational Study

Journals

  1. Williams K, Nikolajski C, Rodriguez S, Kwok E, Gopalan P, Simhan H, Krishnamurti T. Incorporating end-user perspectives into the development of a machine learning algorithm for first time perinatal depression prediction. Journal of the American Medical Informatics Association 2025;32(7):1186 View
  2. Flierman M, Möller E, Vijn V, Engelbert R, Jeukens-Visser M, van Kaam A, Bossen D. An Information App (e-TOP) to Support Parents’ Information Needs During the First Year at Home After Preterm Birth: Development and Usability Study. JMIR Pediatrics and Parenting 2025;8:e75569 View
  3. Jawed A. Leveraging AI Avatars for Safe Sleep Education: Combating SIDS Misinformation Through Interactive, Culturally Responsive Tools. American Journal of Health Education 2026;57(4):298 View
  4. Yousef S, Meaney N, Dowding D, Gasteiger N. Supporting safer sleep: A systematic review of standalone mHealth applications for parents of newborns and infants in the United Kingdom (Preprint). JMIR mHealth and uHealth 2026 View