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Record W7117538932 · doi:10.1186/s12884-025-08429-8

An estimation of the effect of finding nurses helpful on early breastfeeding exclusivity mediated via breastfeeding self-efficacy, using a counterfactual approach and G-computation

2025· article· en· W7117538932 on OpenAlexaff
Alessandra Prioreschi, Shane Anthony Norris, Cindy-Lee Dennis

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2025
Typearticle
Languageen
FieldMedicine
TopicBreastfeeding Practices and Influences
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersNational Institute for Health and Care ResearchDepartment of Health and Social CareWellcome Trust
KeywordsBreastfeedingCounterfactual thinkingPsychological interventionEstimationReproductive medicineObservational study

Abstract

fetched live from OpenAlex

BACKGROUND: Exclusive breastfeeding is recommended for at least the first six months of life, however in South Africa only 32% of mothers are exclusively breastfeeding to six months and discontinuation happens early. Nurses are a key resource for promoting breastfeeding self-efficacy and thus exclusivity, yet mothers often report nurses to have poor attitudes, which deter health seeking behaviour. This study aimed to infer whether perceived support from nurses immediately postpartum was causally related to breastfeeding exclusivity, and specifically whether this effect was mediated via breastfeeding self-efficacy. METHODS: This cross-sectional study recruited mothers from two community clinics in Soweto and collected data on breastfeeding practices, breastfeeding self-efficacy, and mothers' perceived support received from nurses within the first few days following delivery. To estimate the causal effect, G-computation for mediation analysis with Monte Carlo simulation was used. In all cases, 1000 bootstrapped samples were created to tighten the estimates, and bias corrected 95% confidence intervals were presented. RESULTS: Data from 169 participants were included in the analysis. Most participants (55%) scored 70/70 on the breastfeeding self-efficacy scale, and only 14% scored below 56/70 (lowest quartile). Less than half of the women found the nurses helpful 'always'. Most data were collected within 4 days of birth (IQR: 3-7 days), with only 10% being collected after 12 days. While nearly 90% of women were breastfeeding at this time, only 78% were exclusively breastfeeding. The results from the mediation analysis show that there was a total causal effect of finding nurses helpful on breastfeeding exclusivity, whereby finding nurses 'always' helpful resulted in a 14% greater likelihood of exclusively breastfeeding (SE = 0.06, p = 0.03, BC 95% = 0.00 to 0.24). However, this effect was not mediated via breastfeeding self-efficacy (proportion mediated = 7%; NIE = 0.01, BC 95%: -0.00 to 0.05). CONCLUSIONS: There is evidently a need for proper training for healthcare workers in supporting mothers and providing antenatal education and anticipatory guidance around breastfeeding given the impactful role they have on breastfeeding decision making. We recommend that interventions to promote breastfeeding exclusivity need to happen prior to delivery, or immediately upon delivery. Furthermore, all clinics need to enforce the BFHI immediately to provide mothers with a chance at exclusivity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.147
metaresearch head score (Gemma)0.282
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.779

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1470.282
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.013
Bibliometrics0.0030.003
Science and technology studies0.0010.005
Scholarly communication0.0030.003
Open science0.0050.004
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.015
GPT teacher head0.297
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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