Cross-cultural adaptation of the Breastfeeding Self-Efficacy Scale Short Form (BSES-SF) modified for preterm mothers in Brazil
Bibliographic record
Abstract
OBJECTIVES: to conduct a cross-cultural adaptation of the Breastfeeding Self-Efficacy Scale-Short Form (BSES-SF) for mothers of ill and/or preterm infants among Portuguese-speaking mothers in Brazil. METHODS: a methodological study was completed, including the translation of the tool, synthesis of translations, review by experts, synthesis, reassessment of experts, back-translation, pre-test, and validation of the content. The study involved 19 participants, including a translator and experts. In addition, 18 mothers from the target population were included in the pre-test. RESULTS: the equivalences of the opinion obtained by the committee of experts were semantic (85%), idiom (89%), cultural (86%), and conceptual (94%). The content validation coefficient (CVC) on the scale was 0.93 for clarity and understanding; 0.89 for practical relevance; 0.92 for relevance; and the average overall CVC was 0.91. CONCLUSIONS: the scale was translated and adapted to the Brazilian Portuguese language, which maintained the equivalences and confirmed the content validity.
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 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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".