Learning Needs of Postpartum Women: Does Socioeconomic Status Matter?
Bibliographic record
Abstract
BACKGROUND: Little is known about how information needs change over time in the early postpartum period or about how these needs might differ given socioeconomic circumstances. This study's aim was to examine women's concerns at the time of hospital discharge and unmet learning needs as self-identified at 4 weeks after discharge. METHODS: Data were collected as part of a cross-sectional survey of postpartum health outcomes, service use, and costs of care in the first 4 weeks after postpartum hospital discharge. Recruitment of 250 women was conducted from each of 5 hospitals in Ontario, Canada (n = 1,250). Women who had given vaginal birth to a single live infant, and who were being discharged at the same time as their infant, assuming care of their infant, competent to give consent, and able to communicate in one of the study languages were eligible. Participants completed a self-report questionnaire in hospital; 890 (71.2%) took part in a structured telephone interview 4 weeks after hospital discharge. RESULTS: Approximately 17 percent of participants were of low socioeconomic status. Breastfeeding and signs of infant illness were the most frequently identified concerns by women, regardless of their socioeconomic status. Signs of infant illness and infant care/behavior were the main unmet learning needs. Although few differences in identified concerns were evident, women of low socioeconomic status were significantly more likely to report unmet learning needs related to 9 of 10 topics compared with women of higher socioeconomic status. For most topics, significantly more women of both groups identified learning needs 4 weeks after discharge compared with the number who identified corresponding concerns while in hospital. CONCLUSIONS: It is important to ensure that new mothers are adequately informed about topics important to them while in hospital. The findings highlight the need for accessible and appropriate community-based information resources for women in the postpartum period, especially for those of low socioeconomic status.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".