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
Bibliographic record
Abstract
BACKGROUND: The postpartum period represents a critical period for both birthing and nonbirthing parents due to mental health concerns and new caregiving demands. Collaborative care models aim to address these needs, but postpartum care remains fragmented, lacking continuity and holistic support. Baby2Home (B2H) is a digital intervention rooted in the collaborative care model, specifically designed to support parents through their transition into parenthood by addressing their physical, emotional, and psychosocial needs. This intervention seeks to close the gaps left by traditional care models by providing continuous, organized, and accessible support throughout the postpartum period. In our qualitative study of the B2H intervention, we reference the parallel journeys framework and use it as a part of our analysis to evaluate whether mobile health (mHealth) technology addresses the holistic needs (postpartum and psychosocial) of new parents. OBJECTIVE: We aimed to assess how the B2H app supports the holistic needs of new parents and addresses care gaps identified in traditional postpartum services. METHODS: We conducted semistructured interviews with 20 birthing and nonbirthing parents selected through purposive sampling based on their app use. Data were analyzed using the postpartum parallel journeys framework and inductive coding. RESULTS: Our findings demonstrate the comprehensive impact of the B2H intervention in addressing both the physical and psychosocial needs of new parents. B2H supported postpartum care by helping parents navigate uncertainties, enhancing health care provider-parent communication, promoting self-care, and increasing parental self-efficacy. Psychosocial support included symptom identification, timely care manager assessments, coordinated treatment, and transition resources. The app also addressed care gaps by promoting inclusivity for nonbirthing parents, bridging screening and treatment, supporting real-time treatment navigation, and ensuring continuity of care. CONCLUSIONS: We demonstrate that the use of mHealth technology such as the B2H app can effectively support the multifaceted needs of new parents during their postpartum care period. By applying the parallel journeys framework, the research also identifies gaps in care that are addressed by the B2H app, presenting unique opportunities for future development and research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".