A randomized trial of two public health nurse follow-up programs after early obstetric discharge
Bibliographic record
Abstract
Objectives: To determine whether the outcomes of routine home visiting by public health nurses (PHN) after early obstetrical discharge differ from those of a screening telephone call designed to identify mothers who need further intervention. Methods: Primiparas delivering a singleton infant and eligible for postpartum follow-up were randomized to a home visit or screening telephone call. Data were collected by telephone from 733 participants located at two tertiary care centres in Ontario. Outcomes included maternal confidence at two weeks, health problems of the infants between discharge and four weeks postpartum, breastfeeding rates at six months and costs of the two models. Results: Differences between the samples at the two sites necessitated stratified analyses. No differences were detected between the groups in maternal confidence (p=0.96), health problems of infants (p=0.87), or rates of breastfeeding at six months (p=0.22). However, at both sites the cost of routine home visits was found to be higher than that of screening by telephone. Conclusion: Although universal access to postpartum support is important, the results suggest that a routine home visit is not always necessary to identify the women who need it. These results can be generalized only to low-risk women and infants. The need for follow-up after earlydischarge has been recognized bythe American Academy of
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".