Evaluating Breastfeeding Self-Efficacy in Adolescents Attending a Co-Designed Breastfeeding Program: A Prospective Pilot Cohort Study
Bibliographic record
Abstract
Adolescents have lower rates of breastfeeding (BF) compared to older mothers. BF self-efficacy (SE) has been identified as an important factor influencing BF outcomes. An innovative BF program for young women was co-designed and implemented, which included staff training, a prenatal BF class, and BF peer support. The objective of this prospective pilot cohort study was to evaluate the effectiveness of prenatal education and peer support in improving a young mother's BF SE. Participants were pregnant adolescents recruited from a large urban non-profit social service outreach centre. The Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) was administered to participants before and after participating in the BF program. BSES-SF scores were summed to determine a composite score and compared descriptively using median score. Un-aggregated, item-by-item, comparison of pre- versus post-BF program scores were also compared to examine improvements in SE. A total of 20 adolescent mothers (mean age = 16.6) attended the program. An increase in the total BSES-SF score was observed based on descriptively comparing the mean pre- versus post-intervention. Participation in tailored prenatal education classes and a peer-support program was associated with increased BSES-SF. Identifying mothers with low BF SE can enable healthcare professionals to implement targeted interventions in this at-risk population.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".