Perspectives of accessing and providing prenatal nutrition care in a rural First Nations community: a collaborative, qualitative case study
Bibliographic record
Abstract
Women living in rural First Nations communities face challenges accessing adequate nutrition and nutrition care during pregnancy, creating a barrier to achieving optimal maternal, fetal and newborn health outcomes. Key policy documents have highlighted the importance of understanding and giving voice to First Nation women with regard to antenatal programming including nutrition care. First Nation communities are marked by low rates of recruitment and retention of health care providers, as these professionals are often required to provider a broader scope of practice and have a higher workload than their urban counterparts. Understanding both women and provider perspectives is a key step to improving efficacy of antenatal services. This qualitative project is a collaboration between First Nations Health Authority, Haisla Nation, and The University of British Columbia. Using a community-centric, case study framework, we explored the experiences of the birthing population and care providers of accessing and providing nutrition care and programs within the Northern community of Kitamaat Village (Haisla Nation), British Columbia. Data collection consisted of open-ended interviews with 13 pregnant or recently pregnant women and 4 care providers within Haisla Nation. The lead researcher transcribed interview transcripts verbatim and textual data was analyzed using qualitative computer software (nVivo, QRS International Pty. Ltd). Transcripts underwent inductive coding and thematic analysis according to Braun and Clarke. Main themes that resulted from analysis included the perceived value and experience of current antenatal nutrition programs; lack of nutrition advice provided within primary care setting; the role for nutrition specialist within Haisla Nation; and the importance of traditional foods and practices during pregnancy. By gaining insight on how nutrition care is accessed, perceived and provided within Haisla Nation using a community centric model we are able to use the knowledge gained to further the provision of nutrition care during the antenatal period for First Nation women. The success of current programs within this community, as well as the process developed to understand the on the ground experiences have potential to be adapted in other First Nation communities in British Columbia to tailor prenatal nutrition programming across the province.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| 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".