Program for expectant and new mothers: a population-based study of participation
Bibliographic record
Abstract
BACKGROUND: The Manitoba Healthy Baby Program is aimed at promoting pre- and perinatal health and includes two components: 1) prenatal income supplement; 2) community support programs. The goal of this research was to determine the uptake of these components by target groups. METHODS: Data on participation in each of the two program components were linked to data on all hospital births in Manitoba between 2004/05 through 2007/08. Descriptive analyses of participation by maternal characteristics were produced. Logistic regression analyses were conducted to identify factors associated with participation in the two programs. Separate regressions were run for two groups of women giving birth during the study period: 1) total population; 2) those receiving provincial income assistance during the prenatal period. RESULTS: Almost 30% of women giving birth in Manitoba received the Healthy Baby prenatal income supplement, whereas only 12.6% participated in any community support programs. Over one quarter (26.4%) of pregnant women on income assistance did not apply for and receive the prenatal income supplement, despite all being eligible for it. Furthermore, 77.8% of women on income assistance did not participate in community support programs. Factors associated with both receipt of the prenatal benefit and participation in community support programs included lower SES, receipt of income assistance, obtaining adequate prenatal care, having completed high school and having depressive symptoms. Having more previous births was associated with higher odds of receiving the prenatal benefit, but lower odds of attending community support programs. Being married was associated with lower odds of receiving the prenatal benefit but higher odds of participating in community support programs. CONCLUSIONS: Although uptake of the Healthy Baby program in Manitoba is greater for women in groups at risk for poorer perinatal outcomes, a substantial number of women eligible for this program are not receiving it; efforts to reach these women should be enhanced.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".