Accessibility settings

This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (4925) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1718) mHealth for Data Collection and Research (1680) Participatory Design and Participatory Research (511) Mobile Health and Apps for Maternal and Child Health (267) Recruitment of Research Participants (462) Mobile Apps for Pregnancy and Parenting Education (86)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70149, first published .
Pregnant woman uses phone with digital health monitoring interface

Digital Health Platform for Maternal Health: Design, Recruitment Strategies, and Lessons Learned From the PowerMom Observational Cohort Study

Digital Health Platform for Maternal Health: Design, Recruitment Strategies, and Lessons Learned From the PowerMom Observational Cohort Study

Authors of this article:

Toluwalase Ajayi1, 2 Author Orcid Image ;   Jacqueline Kueper2 Author Orcid Image ;   Lauren Ariniello2 Author Orcid Image ;   Diana Ho2 Author Orcid Image ;   Felipe Delgado2 Author Orcid Image ;   Matthew Beal3 Author Orcid Image ;   Jill Waalen3 Author Orcid Image ;   Katie Baca Motes2 Author Orcid Image ;   Edward Ramos2 Author Orcid Image
Article Authors Cited by (6) Tweetations Metrics

Journals

  1. Milan G, Ariniello L, Baca-Motes K, Faksh A, Kueper J, Pandit J, Àjàyí T, Quer G. Association between wearable sensor signals and expected hormonal changes in pregnancy. eBioMedicine 2025;119:105888 View
  2. Yang X, Ning Y, He Y, Wan Nordin N, Chen X. Bridging Knowledge Gaps: Prenatal Education Acquisition and Its Determinants Among Expectant Mothers in Northwestern China. International Journal of Women's Health 2026;Volume 18:1 View
  3. Ajayi T, Kueper J, Waalen J, Ariniello L, Ramos E, Milan G, Baca-Motes K, Williams A, Bullard, L, Robinson A. Woebot for Postpartum Mood and Anxiety: A Randomized Controlled Trial Evaluating Feasibility, Acceptability, and Preliminary Efficacy of a Mobile CBT Intervention (Preprint). JMIR Pediatrics and Parenting 2025 View
  4. Sun Y, Chong M, Zhang J, Guo R, Xu F, Chui P. Digital Health in Midwifery Practice: A Qualitative Review of Midwives’ Experiences and Perceptions. International Nursing Review 2026;73(2) View
  5. Bashir S, Salad H, Abdullahi Y, Abdi Y, Abdi M, Ahmed N, Saidu Musa S, Elehamer N, Musa M, Bolarinwa O, Dada O. Artificial intelligence for predicting and preventing adverse pregnancy outcomes addressing bias and clinical translation. Frontiers in Digital Health 2026;8 View

Books/Policy Documents

  1. Ogbonnaya-Okafor C, Ataguba G, Chan G, Orji R. Persuasive Technology. View