A Toronto Midwifery Practice’s Postpartum Visit Schedule and Chest/ Breastfeeding Rates before and during the COVID-19 Pandemic
Bibliographic record
Abstract
Objective: This study aims to determine whether the alternate midwifery postpartum visit schedule imposed by the COVID-19 pandemic affected the chest/breastfeeding rate of midwifery clients compared to the standard postpartum visit schedule. Methods: Three hundred anonymized records of midwifery clients at a Toronto midwifery practice were analyzed for the total number of postpartum parent–infant visits and method of infant feeding at Day 3, 2 weeks, and 6 weeks postpartum. The pre-pandemic cohort (n1 = 150) gave birth from January to October 2018. The pandemic cohort (n2 = 150) gave birth from April to November 2020. Results: The cohort comparison showed that the average number of postpartum visits during the COVID-19 pandemic remained unchanged. The exclusive chest/breastfeeding rate at 6 weeks postpartum was not significantly different, and it remained high. Conclusion: Midwifery clients and midwives persevered through the COVID-19 pandemic, demonstrating a high commitment to protecting individualized dyad-centred care and in-person chest/breastfeeding support. RÉSUMÉObjectif : Cette étude vise à déterminer si le calendrier alternatif des visites postnatales imposé par la pandémie de COVID-19 a eu une incidence sur le taux d’allaitement maternel des clientes des sages-femmes par rapport au calendrier standard des visites postnatales. Méthodes : Trois cents dossiers anonymisés de clientes d’une pratique de sages-femmes à Toronto ont été analysés afin de déterminer le nombre total de visites postnatales des parents et des nourrissons et la méthode d’alimentation des nourrissons au troisième jour, à deux semaines et à six semaines après l’accouchement. La cohorte pré-pandémique (n1 = 150) a accouché entre janvier et octobre 2018. La cohorte pandémique (n2 = 150) a accouché entre avril et novembre 2020. Résultats : La comparaison des cohortes a montré que le nombre moyen de visites post-partum pendant la pandémie de COVID-19 est resté inchangé. Le taux d’allaitement maternel exclusif à 6 semaines après l’accouchement n’était pas significativement différent et est resté élevé. Conclusion : Les clientes des sages-femmes et les sages-femmes ont persévéré pendant la pandémie de COVID-19, démontrant un engagement fort en faveur de la protection des soins individualisés centrés sur la dyade et du soutien à l’allaitement maternel en personne.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".