Prenatal care experiences of first-time mothers navigating socioeconomic challenges during pregnancy in New Brunswick: a qualitative descriptive study
Bibliographic record
Abstract
BACKGROUND: Mothers facing socioeconomic challenges encounter substantial barriers to consistent, quality prenatal care, essential for reducing adverse birth outcomes. This study explores the barriers and facilitators to accessing prenatal care experienced by socioeconomically disadvantaged first-time mothers in New Brunswick, Canada. METHODS: A qualitative design was used to examine prenatal care experiences among first-time mothers facing socioeconomic disadvantage in New Brunswick. Participants were recruited between February and March 2024 through community organizations, including Family Resource Centres, using purposive sampling. Semi-structured interviews were conducted, transcribed, and analyzed thematically using NVivo 14. RESULTS: Four key themes emerged from the experiences of 11 participants: (i) structural challenges and discontinuity disrupt prenatal healthcare delivery; (ii) social and physical distance constrain access to prenatal services; (iii) prenatal care experiences amplify the emotional dimensions of pregnancy and birth; and (iv) relational interactions shape prenatal service access and quality. Participants described systemic issues including provider shortages, fragmented care, and long wait times. Geographic barriers particularly affected rural participants, creating travel burdens and limiting service access. Emotional dimensions of care were influenced by provider interactions, with negative experiences eroding trust and positive interactions providing emotional anchoring. Informal networks and community-based organizations served as critical facilitators, providing accessible support and bridging gaps in formal systems. CONCLUSIONS: Socioeconomically disadvantaged first-time mothers face compounding barriers to prenatal care in New Brunswick. Addressing these disparities requires integrated public health approaches that coordinate care across providers and settings, expand community-based services, and reduce geographic and financial barriers. Participants relied primarily on informal networks and community organizations rather than formal programs, highlighting needs for improved outreach and service integration to better support vulnerable mothers during pregnancy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".