Understanding the experiences of young, urban, Indigenous mothers-to-be in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Indigenous Peoples comprise the youngest and fastest growing demographic in Canada, with many living in urban-suburban areas. Given higher fertility rates, younger overall ages and higher adolescent pregnancy rates, perinatal research is needed-to inform policymaking and programming throughout pregnancy and childhood. Yet such data remain scarce in British Columbia (BC), Canada. This study therefore aimed to describe the experiences of young, urban, Indigenous mothers-to-be who enrolled in a larger BC early prevention trial designed to reach families experiencing socioeconomic disadvantage. METHODS: This descriptive study utilized baseline data from a trial that enrolled first-time mothers-to-be who met indicators of socioeconomic disadvantage and who were residing in select urban-suburban areas. These indicators included being young (19 years or younger) or having limited income, low access to education, and being single (aged 20-24 years). We described and compared survey data on girls (n = 109; aged 14-19 years) and young women (n = 91; aged 20-24 years) using Chi-square or Student's t-tests. RESULTS: Of the 739 trial participants, 200 or 27% identified as Indigenous and met trial eligibility criteria: limited income (92.9%), limited access to education (67.0%), and/or being single (90.9%). Beyond this, participants reported associated adversities including: unstable housing (63.3%), psychological distress (29.3%), severe anxiety or depression (48.5%), experiences of childhood maltreatment (59.4%) and intimate partner violence (39.5%). Compared to girls, young women reported higher income and educational attainment (p < 0.001), more unstable housing (p = 0.02) and more childhood maltreatment (p = 0.014). Many had recently received primary healthcare (75%), but few had received income assistance (34%). Most (80.5%) reported experiencing four or more adversities. CONCLUSIONS: We present data illustrating that a high proportion of pregnant Indigenous girls and young women engaged with public health and consented to long-term research participation-despite experiencing cumulative adversities. The trial socioeconomic screening criteria were successful in reaching this population. Girls and young women reported relatively similar experiences-beyond expected developmental differences in income and education-suggesting that adolescent maternal age may not necessarily infer risk. Our findings underscore the need for Indigenous community-led services that address avoidable adversities starting in early 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".