Qualitative Evaluation: Partners in Inner-city Integrated Prenatal Care Project in Winnipeg, Canada
Bibliographic record
Abstract
Background Our previous research demonstrated high rates of inadequate prenatal care (PNC) among inner-city women in Winnipeg, Canada and identified barriers and facilitators related to use of PNC. Building on these findings, service providers, policy makers and researchers collaborated to develop the Partners in Inner-city Integrated Prenatal Care (PIIPC) Project, with the goal of reducing inequities in use of PNC. The objective of this qualitative component of the larger mixed-methods study was to explore the perspectives of women and health care providers about the PIIPC project. Methods A qualitative descriptive design was used. In-depth individual interviews were conducted with 22 postpartum women and 26 health care providers who participated in the PIIPC project. Purposeful and maximum variation sampling strategies were used. Interviews were digitally recorded and transcribed. Content analysis was used to identify themes and categories. Results The majority of women were single, low income, and self-identified as Indigenous. Women described access to PNC as convenient and coordinated. Key components included flexible scheduling and receiving incentives and assistance with transportation. Women commented on positive relationships with health care providers, using descriptors such as helpful, respectful, and nonjudgmental. A variety of health care providers participated in the interviews (physicians, midwives, nurses, social workers). Themes included better understanding of other programs, improved communication between programs, benefits of team work, and positive changes in service delivery (e.g., more accessible and convenient). Conclusions The PIIPC project reduced barriers to care and facilitated communication between programs, resulting in improved use of PNC by inner-city women. This project exemplifies how an integrated knowledge translation approach and building successful partnerships can contribute to health system improvements. Key messages The Partners in Inner-city Integrated Prenatal Care project was successful in reducing inequities in use of prenatal care among women who experience social and economic disadvantage Previous research findings were used to inform an integrated knowledge translation approach to design health system improvements that resulted in improved use of prenatal care by inner-city women
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".