ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2020
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Understanding the Implications of mHealth Technology in Collaborative Care Programs and Its Role in Supporting Postpartum Care: Qualitative Interview Study of the Baby2Home Intervention Using the Parallel Journeys Framework.JMIR pediatrics and parenting · 2025Article
- Enhancing Digital Health Development Through Speech Act Theory: Application to Peripartum Depression Management.Studies in health technology and informatics · 2025Article
- A pilot acceptability evaluation of MomMind: A digital health intervention for Peripartum Depression prevention and management focused on health disparities.PLOS digital health · 2024Article
- Digital health technologies for high-risk pregnancy management: three case studies using Digilego framework.JAMIA open · 2024Article
- Digital health technologies for peripartum depression management among low-socioeconomic populations: perspectives from patients, providers, and social media channels.BMC pregnancy and childbirth · 2023Article
- Analysis of Online Peripartum Depression Communities: Application of Multilabel Text Classification Techniques to Inform Digitally-Mediated Prevention and Management.Frontiers in digital health · 2021Article
- Towards Digestible Digital Health Solutions: Application of a Health Literacy Inclusive Development Framework for Peripartum Depression Management.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Digital health technologies offer unique opportunities to improve health outcomes for mental health conditions such as peripartum depression (PPD), a disorder that affects approximately 10-15% of women in the U.S. every year. In this paper, we present the adaption of a digital technology development framework, Digilego, in the context of PPD. Methods include mapping of the Behavior Intervention Technology (BIT) model and the Patient Engagement Framework (PEF) to translate patient needs captured through focus groups. This informs formative development and implementation of digital health features for optimal patient engagement in PPD screening and management. Results show an array ofPPD-specific Digilego blocks ("My Diary", "Mom Talk", "My Care", "Library", "How am I doing today?"). Initial evaluation results from comparative market analysis indicate that our proposed platform offers advantageous technology aspects. Limitations and future work in areas of interdisciplinary care coordination and patient engagement optimization are discussed.
Indexed as
Identifiers
33936518PMC8075464W3158592316What OpenQuestion holds
Registered trials
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.